In machine learning, a large number of known training samples can be used to construct a classification model, i.e. a classifier, and then the constructed classifier is used to predict unknown data. The classifier can be applied in many scenarios, for example, since there are more and more spam pages produced due to network cheating, which seriously affects the retrieval efficiency of a search engine and user experience, anti-cheating has become one of the most important challenges faced by search engines; a classifier can be constructed using labeled normal data and cheating data, so as to identify network data. In the prior art, a constructed classifier can be used to predict data, so as to obtain a classification result.
However, when a single classifier is used, the accuracy of the classification result of the data predicted thereby is not high.